Data Mining

This book constitutes the refereed proceedings of the 19th Australasian Conference on Data Mining, AusDM 2021, held in Brisbane, Queensland, Australia, in December 2021.*
The 16 revised full papers presented were carefully reviewed and selected from 32 submissions. The papers are organized in sections on research track and application track.

*Due to the COVID-19 pandemic the conference was held online.

Inhalt
Research Track.- Parallel Nonlinear Dimensionality Reduction Using GPU Acceleration.- Taking the Confusion out of Multinomial Confusion Matrices and Imbalanced Classes.- Sharpshooting Most Beneficial Part of AUC for Detecting Malicious Logs.- A Drift Aware Hierarchical Test based Approach for Combating Spammers in Online Social Networks.- Hospital Readmission Prediction Using Semantic Relations Between Medical Codes.- HFM++: An Enhanced Holographic Factorization Machine for Recommendation.- Deep Learning for Bias Detection: From Inception to Deployment.- Exploring Fusion Strategies in Deep Learning Models for Multi-modal Classification.- Application Track.- Chameleon: A Python Workflow Toolkit for Feature Selection.- PostMatch: A Framework for Efficient Address Matching.- Detection of Classical Cipher Types with Feature-Learning Approach.- SOMPS-Net: Attention based Social Graph Framework for Early Detection of Fake Health News.- How to Read the News: A Study of How Sentiment Effects Financial Markets.- Investigation of Topic Modelling Methods for Understanding the Reports of the Mining Projects in Queensland.- A Semi-Automatic Data Extraction System for Heterogeneous Data Sources: A Case Study from Cotton Industry.- Nonnegative Matrix Factorization to Understand Spatio-Temporal Traffic Pattern Variations during COVID-19: A Case Study.